Fiscal policy and CO2 emissions of new passenger cars in the EU
This version: 4 February 2015 *
Reyer Gerlagh, Tilburg University, Netherlands
Inge van den Bijgaart, Tilburg University, Netherlands
Hans Nijland, PBL Netherlands Environmental Assessment Agency, Netherlands
Thomas Michielsen, CPB Netherlands Bureau for Economic Policy Analysis, Netherlands
Abstract
To what extent have national fiscal policies contributed to the decarbonisation of newly sold
passenger cars? We construct a simple model that generates predictions regarding the effect of fiscal
policies on average CO2 emissions of new cars, and then test the model empirically. Our empirical
strategy combines a diverse series of data. First, we use a large database of vehicle-specific taxes in
15 EU countries over 2001-2010 to construct a measure for the vehicle registration and annual road
tax levels, and separately, for the CO2 sensitivity of these taxes. We find that for many countries the
fiscal policies have become more sensitive to CO2 emissions of new cars. We then use these
constructed measures to estimate the effect of fiscal policies on the CO2 emissions of the new car
fleet. The increased CO2-sensitivity of registration taxes have reduced the CO2 emission intensity of
the average new car by 1,3 percent, partly through an induced increase of the share of diesel-fuelled
cars by 6,5 percentage points. Higher fuel taxes lead to the purchase of more fuel efficient cars, but
higher annual road taxes have no or an adverse effect.
JEL Classification Numbers: H30, L62, Q48, Q54, Q58, R48
Key Words: vehicle registration taxes, fuel taxes, CO2 emissions
*.
We are grateful for comments from Alice Ciccone, Georgios Fontaras, Herman Vollebergh, Josh Linn,
Lutz Kilian, Stephan Leinert, Rebecca Scott, Christian Huse, Anco Hoen, Robert Kok, Gerben Geilenkirchen,
Justin Dijk.
1
1
Introduction
Transport accounts for about 23% of energy-related CO2 emissions (Sims and Schaeffer,
2014), that is 15% of global greenhouse gas emissions (Blanco, Gerlagh and Suh, 2014).
Within the EU, passenger cars represent about 12% of EU CO2 emissions. 2 In 1995, the
European Commission launched a strategy to reduce carbon dioxide emission intensity (i.e.
emissions per kilometer) for new cars sold in the European Union. Since then, the emission
intensity of new sold cars has come down remarkably, especially since 2007 (Figure 1). In
2011, the strategy was updated with a proposal to reduce EU transport greenhouse gas
emissions by 60%, by 2050 as compared to 1990 levels (European Commission, 2011).
The strategy is based on three pillars. The first pillar targets car manufacturers,
requiring them to reduce the average emissions of new cars. The associated directive,
established in 2009, aims to decrease the average emissions of new sold cars to 130
gCO2/km by 2015, and 95 gCO2/km by 2020 (European Parliament and Council, 2009). 3
The second pillar aims to ensure that the fuel-efficiency information of new passenger cars
offered for sale or lease in the EU is made available to consumers to facilitate an informed
choice. The third pillar aims to influence consumer’s vehicle purchase choices by
increasing taxes on fuel-inefficient cars relative to fuel-efficient cars. For our analysis, tax
instruments are divided in three categories related to the purchase, ownership and use of a
car: the registration tax, the annual road tax and annual income tax for company cars, and
the fuel tax. 4
The three pillars are expected to reinforce each other. Increasing the tax burden on
fuel-intensive cars, relative to the burden on fuel-efficient cars (third pillar), and providing
information (second pillar) is expected to increase the sale of fuel-efficient cars, which in
turn makes it more profitable for car manufacturers to produce fuel efficient cars (the first
2
3
http://ec.europe.eu/clima/policies/transport/vehicles/cars/index_en.htm
All data on CO2 emission/km in this study are determined according to the NEDC guidelines
(New European Driving Cycle, the prescribed European test cycle).
4
We use purchase tax, registration tax, and acquisition tax interchangeably. Similarly, road
taxes and annual taxes refer to the same fiscal instrument. Due to a lack of data, we did not
include annual income tax for company cars in our analysis. See Section 7.
2
pillar). Our study assesses the effectiveness of the third pillar. We construct measures for
the level and CO2 sensitivity of car taxes so that we can compare different tax regimes over
countries and years, and we then use these constructed measures to evaluate the effects of
these taxes. Figure 2 presents the EU15-average for two of our constructed variables,
showing the implementation of the third pillar policy; the figure presents the average CO2
sensitivity of registration taxes in the EU15 for petrol and diesel cars. We elaborate on the
construction of this variable in Section 3.2. On the vertical axis, we plot the increase in the
registration tax in Euros, for each increase in CO2 emission intensity (gCO2/km), if all other
car features remain constant. The figure shows that an increase of the emissions intensity
by 10g CO2/km implies, on average, an increase in the registration tax of about €130 in
2001, and €350 in 2010. 5
Taxes, including car taxes, are decided on a national level, though. In 2005, the
European Commission proposed to harmonise national vehicle registration and annual
road taxes (European Commission, 2005), but the proposal was rejected by the member
states. Yet, over the years, many EU-countries implemented the third strategy pillar,
greening the car taxes though either a revision of purchase taxes, company car taxes or
annual road taxes. Figure 3 shows the emissions intensity of petrol cars in the EU15
countries (EEA 2013, Eurostat 2014), and thus presents the effect of changing policies and
changes in other variables. Newly sold passenger cars in the different EU15 countries have
quite different levels of CO2-emissions, but there is a robust downward trend, again
especially since 2007. 6 In 2010, average emissions from new cars ranged from 130
gCO2/km (Portugal) to 153 (Germany). 7 Since then, emissions have continued to decrease.
5
All prices are deflated with 2010 as base year. For comparison, note that the EU from 2019
will levy a penalty of €95 per gCO2/km if the average CO2 emissions of a manufacturer's fleet
exceed its limit value.
6
The anticipation of regulation EC/443/2009 (European Parliament and Council, 2009) is a
7
We did not use so-called ‘super credits’ to calculate average emissions (according to EU-
possible explanation for the downward trend after 2007.
regulation 443/2009, super credits only apply as of 2012)
3
Figure 1: CO2 emission-intensity for new cars, EU15 average 8 (Source: Campestrini and
Mock, 2011)
8
The figures averages over 15 countries without weights.
4
Figure 2: CO2 sensitivity of registration taxes averaged over EU15 9
9
A value of 20 €/(gCO2/km) on the vertical axis means that if two cars are identical, in
technical characteristics and tax-exclusive price, but one of the two cars emits 30 gCO2/km
more, then the less fuel-efficient car will pay 20[€/(gCO2/km)] x 30 [gCO2/km] =600€ higher
taxes. The figure uses unweighted averages of the fiscal regimes over all countries. The
numbers are reported in Section 8.2, Table 5.
5
Figure 3: CO2 emission-intensity for new petrol cars, by country (Source: Campestrini and
Mock, 2011)
The figure also shows substantial differences across countries. CO2 emissions of new cars
have declined most rapidly in Sweden and Denmark. There are various possible
explanations for the differences between countries, and changes over time in the fuel
efficiency. For example, the fall in Sweden’s emission intensity in Figure 3 may be
attributed to domestic policies (Huse and Lucinda, 2013), or to convergence to the EU
average, whereas Denmark’s move from being average to becoming one of the most fuelefficient countries might be the consequence of its aggressive car tax policies. Overall, we
can sort these explanations into five categories. The first category relates to the EU’s first
pillar, which requires manufacturers to sell more fuel efficient cars. For this reason, the
portfolio of cars available for purchase is expected to become more fuel-efficient over time.
Second, the type of cars bought and their fuel efficiency may partly be explained by trends
in consumer preferences. The EU second pillar is related to this cateogory. Third is fiscal
policy on registration and road taxes, related to the third pillar. Countries have developed
widely different fiscal policies aimed at promoting fuel-efficient cars. Some countries have
6
much more aggressive policies vis-a-vis other countries, and countries moving in the same
direction still implemented their policies in different years. Fourth are fuel taxes, which
differ substantially between countries, and many countries have seen changes in fuel taxes.
Fifth are income and the economic crisis. Higher incomes are associated with larger cars,
and lower incomes with smaller, more fuel-efficient cars. In addition, the economic crisis
hit the countries very differently. Those countries hit hardest by the crisis are expected to
see – all else equal – the largest drop.
In this paper, we focus on the third cause, associated with the third pillar. That is, we
address the following research question: to what extent have national fiscal policies
contributed to the decarbonisation of newly sold passenger cars? We construct a simple
model of a representative agent to generate predictions regarding the effect of fiscal
policies on average CO2 emissions of new cars. We study changes at the aggregate level and
are interested in differences between countries and changes over time within countries.
That is, the model and our econometric analysis do not provide a detailed micro
foundation of consumers’ decisions; see Berry et al. (1995) or Meerkerk et al. (2014) for
such an analysis. After presenting the model, we build a dataset in which we compare
vehicle tax systems across 15 countries over the years 2001-2010. We use a dataset of
vehicle-specific taxes, and use these data to characterize each country’s tax system at year t
with regards to the average registration and road tax, and the sensitivity of the taxes with
respect to the car CO2 emissions. We differentiate taxes by petrol and diesel, so that we
construct 8 variables to provide an elaborate characterization of a country’s vehicle tax
system for a given year. Both the construction of the multiple tax proxies and the multi-
country sample mark important contributions to the empirical literature, which typically
has considered a single-country single-event (Hennesy and Tol 2011, Huse and Lucinda
2013, Ciccone 2014, D’Haultfoeuille et al. 2014, Cropper and Chugh 2014).
The constructed variable are used to empirically study the effect of the fiscal
treatment, especially the car purchase tax, on the fuel efficiency of newly sold cars. We
identify the effect by considering dynamic differences between countries in car taxes and
in emission intensities. We control for static differences between countries through
country fixed effects, control for income and for common dynamic patters (e.g. EU policies)
through time fixed effects. We can identify the effect of fiscal policies on car sales as some
countries have consistent low purchase taxes (<30%) that are not very sensitivity to CO2
emissions (Belgium, France, Germany, Italy, Luxembourg, Sweden, United Kingdom), while
7
Spain has low purchase taxes but these have become substantially more CO2 sensitive over
the period 2001-2010. Greece has high purchase taxes (>30%) but these became less CO2
sensitive over the years, and the remaining countries (Austria, Denmark, Finland, Ireland,
Netherlands, Portugal) have relatively high purchase taxes (>30%), with a CO2 component
that substantially increased over the years (>10 €/(gCO2/km)), though the countries differ
substantially. Our empirical strategy is based on the correlation between the uneven
developments in taxes and patterns in the emission intensities for these countries.
2
Literature
There is an emerging empirical literature on the effects of fiscal policies on the fuelefficiency of newly sold cars. The general finding is that fiscal policies are an effective tool
to influence car purchase decisions. In addition, the literature establishes that purchase
taxes are more effective than annual (road) taxes, and that tax reform can cause sizable
petrol-diesel substitution.
A strong example of the responsiveness of car purchases to fiscal policies is
provided by D’Haultfoeuille et al. (2014). They assess the effect of the system of fees and
rebates that existed in France from December 2007 to December 2009. In this system,
owners of fuel efficient cars could receive a tax rebate of up to 1000 euros whereas fuel
inefficient car owners had to pay a fee of up to 2600 euros. The precise rebate and fee
thresholds showed up remarkably in the sales for different car types, with large sales
increases just below and drops just above the thresholds.
The effectiveness of car taxes can depend on the subtle features of the policy
adopted. The theory of rational choice for car purchases assumes that consumers fully
internalize both the expected cost in terms of annual road and fuel taxes, as well as
purchases taxes. Empirical evidence however suggests bounded rationality. Consumers do
not exploit all available information equally, and tend to give more weight to short-term
costs and benefits, known as "consumer myopia” or nearsightedness (DellaVigna, 2009).
For example, when deciding on whether to purchase a more fuel efficient car, consumers
tend to calculate the expected savings in fuel costs only for about three years (see Greene
et al., 2005; Kilian and Sims, 2006; Greene et al., 2013). This nearsightedness is considered
a main reason why, compared to annual taxes, vehicle acquisition taxes are more effective
in directing consumers’ buying decisions (Brand et al., 2013; Gallagher and Muehlegger,
2011; Klier and Linn, 2012; van Meerkerk et al., 2014).
8
Another phenomenon identified by the literature is the substitution between
petrol and diesel cars. When Ireland differentiated its purchase and annual road taxes
according to CO2 emission intensities, sales of smaller cars did not go up. Instead, sales of
diesel cars increased at the expense of large petrol cars (Hennesy and Tol, 2011, Leinert et
al., 2013). This unanticipated shift towards diesel cars reduced the average CO2 emissions
by 13 percent in the first year after the tax reform (Rogan et al., 2011). Less advantageous,
it also raised NOx emissions (Leinert et al., 2013). The vehicle acquisition tax reform in
Norway in 2007 resulted in a drop in CO2 emissions of newly sold cars by 6 gCO2/km in the
short run, mainly caused by an increase of diesel market share by almost 23 percentage
points (Ciccone, 2014). The tax reform in Denmark in 2007 contributed to the sales of
more fuel-efficient cars in the years thereafter. Yet, Mabit (2014) argues that the biggest
contribution to the sales of fuel-efficient cars is probably not the tax reform, but
technological improvements.
All research discussed above analyses the effect of specific vehicle tax policies in a
single country. Hence, these papers cannot control for year-specific effects and the results
are not easily generalizable. Our empirical analysis does not consider a single-event in one
country, yet studies more broadly the fiscal treatment of car purchases and ownership in
relation to car emissions. There are some previous cross-country and panel-data studies on
the effect of fuel prices on fuel efficiency (Burke and Nishitateno 2013, Klier and Linn
2013). The effect of the registration and road tax level on car purchases is previously
studied in Ryan et al. (2009), who use a panel structure for EU countries. They conclude
that vehicle taxes, notably registration taxes, are likely to have significantly contributed to
reducing CO2 emission intensities of new passenger cars. Ryan et al. (2009) focus on the
average level of registration taxes in a country. 10 We take this analysis one step further by
constructing measures of the CO2 sensitivity in addition to the level of registration and
road taxes. This allows us to exploit differences between EU countries in the stringency
and timing of climate-related vehicle fiscal policies. An important part of our study is thus a
10
Note that Ryan et al. (2009) weigh the registration tax measure by vehicle sales, so that in
their analysis the right-hand-side variable depends on policy outcomes. To prevent dependency
of right-hand variables on policy outcomes, we construct tax measures that do not use sales for
weighing; see footnote 13.
9
more comprehensive characterization of the vehicle tax system that can be used to
compare differences across countries and changes over time, based on a large dataset of
country-year-vehicle specific prices inclusive and exclusive of taxes.
3
Model
We illustrate the effect of vehicle purchase taxes on the average emission intensity with a
simple model. We consider two car types. A representative consumer maximises (expected
future) utility u dependent on the current purchase of cars, q1 and q2, and income m net of
purchase expenditures x:
max𝑞1,𝑞2 𝑢(𝑞1 , 𝑞2 , 𝑚 − 𝑥) s.t. 𝑠. 𝑡. 𝑝1𝑐 𝑞1 + 𝑝2𝑐 𝑞2 = 𝑥.
(1)
where 𝑝𝑖𝑐 are costs per quantity, including registration taxes as well as future variable costs
and annual taxes. The utility function satisfies the standard assumptions on continuity,
differentiability, positive derivatives, and concavity. We also assume that both types are
normal goods (increasing consumption with increasing income, decreasing consumption
with increasing prices) and that the total budget for cars, 𝑥, increases in total income, 𝑚.
We do not model consumers’ care about the environmental performance of cars as
such (see Achtnicht 2012 for an analysis along those lines), but focus on the effects of
government instruments geared to direct consumers’ choices. We assume that the tax is
fully shifted to consumers, 11 so that the consumer price of cars is
𝑝
𝑝𝑖𝑐 = (1 + 𝜏𝑖 )𝑝𝑖 ,
(2)
𝑝
where 𝜏𝑖 is a type-specific ad valorem tax and 𝑝𝑖 is the producer price.
11
We abstract here from strategic pricing by car manufacturers. Though this is important as a
mechanism, our results below will hold as long as the car manufacturers pass-through part of
taxes. In general, ad valorem taxes may be under- or overshifted under Bertrand competition
with differentiated products (Anderson, De Palma and Kreider, 2001). If car manufacturers
differentiate prices between countries so as to partly compensate taxes, the effect of fiscal
measures will be reduced, and our coefficients will become smaller and less significant.
10
The tax 𝜏𝑖 consists of a uniform component 𝜑 and an environmental component,
where 𝜃 is a relative weight of the environmental component. The two car types have
different emission intensity, say grams of CO2 per km, which we denote by 𝛽𝑖 . Without loss
of generality, let 𝛽2 > 𝛽1 , for example because car type 2 is more spacious, has more
weight, or is more fancy. The type-specific tax becomes:
𝜏𝑖 = 𝜑 + 𝜃𝛽𝑖 .
(3)
We are interested in the effect of changes in car taxes on the average CO2 intensity of the
car fleet, which we define as
𝐵=
𝛽1 𝑞1 +𝛽2 𝑞2
.
(4)
= 𝜑 + 𝜃𝐵.
(5)
𝑞1 +𝑞2
Policy can change the uniform component of the car tax, 𝜑, the environmental component,
θ, or both. We define the average car-tax, given by
𝑇=
𝜏1 𝑞1 +𝜏2 𝑞2
𝑞1 +𝑞2
so that we can study shifts in the tax structure while keeping a constant overall tax rate. It
is intuitive that an increase in the weight of car-feature θ, while keeping the average tax
rate T constant, will decrease the average emission-intensity of the cars.
Proposition 1. An increase in the weight of environmental performance in taxes, θ, while
keeping average total taxes T constant, will decrease the average CO2 intensity B:
𝑑𝐵
𝑑𝜃
< 0.
(6)
Proof. The policy in the proposition increases the price of the relatively emission-intensive
car and decreases the price of the more fuel-efficient car. The result follows immediately
from the assumption that both car types are normal goods. Q.E.D.
Thus tilting the car taxes to become more CO2-dependent will make the car fleet more CO2-
efficient. The effect of an overall car tax increase depends on the comparative income
elasticity of the two car types.
11
Proposition 2. If the environmental tax component 𝜃 is sufficiently small, then feature B
decreases with an overall tax increase 𝜑 (or equivalently an increase in T) if and only if the
less fuel-efficient car type has higher income elasticity:
𝑑𝐵
𝑑φ
Proof.
Consider
𝜕𝑞2 𝑚
𝜕𝑚 𝑞2
>
𝜕𝑞1 𝑚
𝜕𝑚 𝑞1
<0⇔
⇔
𝜕𝑞2 𝑚
𝜕𝑚 𝑞2
𝜕𝑞2 𝜕𝑥 𝑚
𝜕𝑥 𝜕𝑚 𝑞2
>
>
𝜕𝑞1 𝑚
𝜕𝑚 𝑞1
𝜕𝑞1 𝜕𝑥 𝑚
𝜕𝑥 𝜕𝑚 𝑞1
.
⇔
(7)
𝜕𝑞2 𝑚
𝜕𝑥 𝑞2
>
𝜕𝑞1 𝑚
𝜕𝑥 𝑞1
⇔
𝜕𝑞2 𝑥
𝜕𝑥 𝑞2
>
𝜕𝑞1 𝑥
𝜕𝑥 𝑞1
.
When 𝜃 = 0, an increase in 𝜑 is equivalent to a decrease in the budget for cars. Because
𝜕𝑞 φ
type 2 has a larger income- and budget elasticity �− 𝜕φ2
𝑞2
𝜕𝑞 φ
> − 𝜕φ1 �, the average CO2𝑞
1
intensity B goes down. By continuity, the result also holds for 𝜃 sufficiently small. Q.E.D.
The typical hypothesis asserts that demand for luxurious cars is more income-elastic
(Mannering and Winston, 1985). Larger cars, which are also emission-intensive, tend to be
more comfortable. For example because they offer more storage and lower occupant
fatality rates in vehicle-to-vehicle crashes – attributes that are more easily dispensable
than a car’s basic transportation service. It thus seems plausible that demand for spacious
cars will react more strongly to an equiproportional price increase. The proposition then
predicts a decrease in the average pollution intensity if the uniform tax 𝜑 increases.
For high environmental taxes 𝜃 the effect may be reverted, as an increase in the
uniform tax rate 𝜑 can then represent a fall in the relative price of less fuel-efficient cars. As
we will see however, the relative importance of the environmental component in total car
taxes is modest in European countries, so that the proposition’s condition seems to apply.
4
Data
Here we describe the data used for the empirical analysis. The dependent variable of
interest is the average CO2 intensity of newly purchased vehicles, which depends on
substitution patterns between more and less fuel efficient cars, but also on common fuel
efficiency improvements over all cars, which in our econometric strategy is absorbed by
time fixed effects. The main explanatory variables are fuel taxes and the two coefficients
used in the model in Section 3: the average level of registration and annual road taxes, and
12
their CO2 sensitivity. Here, we define the vehicle registration tax as all one-off taxes paid at
the time the vehicle is registered, which is usually the time of acquisition. For road taxes,
we include all annual recurrent taxes of vehicle ownership. We construct these data for
each country, year and fuel type in our sample using a detailed database with vehicle
registration taxes and road taxes at vehicle-country-year level.
4.1
Data sources
Our first data source is a set of manufacturer price tables as supplied by the European
Commission (2011a). These tables form an unbalanced panel with 11930 observations on
prices and registration taxes, across 204 car types, 20 countries (15 countries up to 2005)
over the years 2001-2010. Petrol cars make up about two-third of all observations. This
source includes the retail price data per country inclusive and exclusive of the registration
tax, and allows us to construct the vehicle-country-year specific registration tax. As of
2011, the European Commission no longer collects data on automobile prices. As these
prices are a crucial part of our analysis, our series end in 2010. Next we construct vehicle-
country-year specific road taxes using our second data source: the ACEA (2010) tax guides
and the European Commission (2011a) passenger car dataset. The construction of the
country registration and annual tax dataset is an important extension compared to Ryan et
al. (2009), and enables us to differentiate between average taxes and the CO2 sensitivity of
vehicle-related taxes. We also take information on fuel taxes from the ACEA tax guides.
Because most cars are petrol or diesel, we restrict our sample to these two fuel types. Sales
data play no role in the construction of the country tax data sets.
The next dataset, from Campestrini and Mock (2011), contains information on the
CO2 intensity of the newly purchased diesel and petrol cars (CO2 emissions in g/km,
weighted by sales, see also Figure 1) and the shares of diesel cars (See Figure 6 in the
appendix Section 8.3). We have this information for the EU15 countries, from 2001-2010.
Lastly, data on nominal per capita GDP is taken from Eurostat (2014). We deflate all prices
(sales prices, taxes, GDP) using a common EU15 price deflator. 12
12
The deflator is constructed using a weighted average of the EU15 countries’ individual
inflation
rates,
according
to
standard
EU
https://www.ecb.europa.eu/stats/prices/hicp/html/index.en.html.
13
methodology.
See
4.2
Constructing country average and CO2 sensitivity of car taxes
Countries have widely divergent rules for registration and road taxes. In some countries,
vehicle registration taxes are based on CO2 emissions, in others, the cylindrical content is
used to compute the tax, or the sales price of the car. In many instances, registration taxes
combine multiple variables. Rules for annual road taxes vary even more across Europe.
Some countries base their annual tax on a car’s engine power (in kW or hp), while other
countries use cylinder capacity, CO2 emissions, weight and exhaust emissions. In addition
to the dispersion between countries, for both registration and road taxes, many countries
have changed their policies over the period 2001-2010; they adopted (temporary)
discounts for fuel efficient cars, or additional charges for cars exceeding specified
standards. We compare tax systems across countries by characterizing each country’s tax
system at year t by the two coefficients used in our model in Section 2. The first coefficient
describes the country-year average tax, the second the CO2 sensitivity of the tax. Both
variables are computed for both the registration and road tax, and for petrol and diesel. We
thus construct 8 variables that characterize a country’s vehicle tax system for a given year.
We now provide the details. Let CO2it be the CO2 intensity of car-type i in year t,
𝜏𝑐𝑖𝑡 the (registration or road) (percentage) tax in country c, and let δcit be the index {0,1}
identifying whether the data are available for country c. For the sake of exposition, we do
not use subscripts for fuel and tax type (registration versus road). We construct the
country-specific average CO2 intensity and average tax rate (denoted by bars on top over
the variables): 13
������𝑐𝑡 = ∑𝑖 𝛿𝑐𝑖𝑡𝐶𝑂2𝑖𝑡
𝐶𝑂2
∑
𝜏̅𝑐𝑡 =
13
𝑖 𝛿𝑐𝑖𝑡
∑𝑖 𝛿𝑐𝑖𝑡 𝜏𝑐𝑖𝑡
∑𝑖 𝛿𝑐𝑖𝑡
(8)
(9)
In the construction of our tax system variables we do not weigh by sales, to prevent our
description of the tax system from being contaminated by the subsequent effects of that same
tax system. The tax system may of course affect sales, and thereby the average CO2 intensity of
new cars. This is discussed in Section 6.
14
That is, the typical car for a country has emissions ������
𝐶𝑂2𝑐𝑡 and pays a tax rate 𝜏̅𝑐𝑡 . We
subsequently calculate the CO2-sensitivity of the tax by comparing how much taxes
increase when CO2 emissions increase, on average, and weighted:
𝐶𝑂2𝑇𝐴𝑋𝑐𝑡 =
∑𝑖 𝑤𝑐𝑖𝑡 (𝜏𝑐𝑖𝑡 −𝜏�𝑐𝑡 )
������𝑐𝑡 )
∑𝑖 𝑤𝑐𝑖𝑡 (𝐶𝑂2𝑐𝑖𝑡 −𝐶𝑂2
(10)
Where weights are given by the deviation from the average CO2 intensity:
𝑤𝑐𝑖𝑡 = (𝐶𝑂2𝑐𝑖𝑡 − ������
𝐶𝑂2𝑐𝑡 )
(11)
The squared weights ensure that the denominator in (10) is strictly positive, and that the
CO2 sensitivity is mainly determined by the tax-differences between the fuel-efficient and
fuel-intensive cars.
Yet, if we want to determine a country’s tax pressure and compare between
countries, we should not consider the tax of the typical car for that country, but the tax for
a typical car that is the same over all countries. Thus, we construct the (virtual) tax rate
�𝑡 that is typical for the set of all
that would apply to a car with a CO2-emission profile 𝐶𝑂2
countries:
�𝑡 = ∑𝑐,𝑖 𝛿𝑐𝑖𝑡𝐶𝑂2𝑐𝑖𝑡
𝐶𝑂2
∑
𝑐,𝑖 𝛿𝑐𝑖𝑡
�𝑡 − ������
𝑇𝐴𝑋𝑐𝑡 = 𝜏̅𝑐𝑡 + 𝐶𝑂2𝑇𝐴𝑋𝑐𝑡 (𝐶𝑂2
𝐶𝑂2𝑐𝑡 )
(12)
(13)
The above method generates 8 variables for each country-year pair. The precise
interpretation depends on the details of the input variables, CO2it and τcit. If CO2 emissions
are measured linearly in [gCO2/km], and taxes in euros, then 𝜏̅𝑐𝑡 is the average tax in euros
[€] while CO2TAXct is the increase as measured in [€/(gCO2/km)]. If taxes are measured ad
valorem, then 𝜏̅𝑐𝑡 is the average tax rate in percentages while CO2TAXct is the increase in
the tax rate per gCO2/km. Our preferred specification uses the logarithm of one plus tax
rates and the logarithm of CO2 emissions, so that variables are interpretable as elasticities,
and (with time fixed effects) the construction is independent of price levels. In this case, a
decrease of the variable CO2t by 0.01 means that emissions have come down by 1%. A
decrease of the variable 𝜏̅𝑐𝑡 of 0.01 means that the tax rate for the typical car has fallen by
1%. If two car types are completely identical (including prices at the factory gate), but one
15
car is 10% more fuel efficient, then the consumer price of the more fuel-efficient car is 0.1*
CO2TAX per cent below the consumer price of the more fuel-intensive car. All estimations
in the main text are based on the double-log variables. We have reproduced our results for
a linear model, which is presented in the appendix, Section 8.2. The appendix also provides
the equations with more elaborate references to the details of taking logarithms.
Figure 4 below shows a typical breakdown of the vehicle registration tax rate in its
level and CO2 sensitivity. The charts show the registration taxes paid in the Netherlands, in
2001 (left) and 2010 (right), for a series of petrol (upper) and diesel (lower) cars. The dots
are observations for individual car types, described at the beginning of Section 3.1. The
lines present the ‘predicted’ tax rates based on the two proxy variables TAX and CO2TAX
constructed above. As is immediately visible from the left and right panels, the tax rate has
become more sensitive to CO2 emissions between 2001 and 2010, that is, the slope of the
line has increased. Figure 5 shows the decomposition of the tax in its average tax rate and
the CO2 tax over the years 2000-2011. The average registration tax rate for petrol cars
started at about 50 per cent, and sharply dropped in the last years reaching about 47 per
cent in 2010 and 40 per cent in 2011. The CO2 sensitivity of registration taxes however has
increased substantially for both petrol and diesel cars between 2000 and 2011. Figure 4
(panel in top-right corner) illustrates this shift. Various tax breaks for fuel-efficient cars
came into force, which substantially increased the CO2 sensitivity of taxes, from about 10%
to 25% (see Figure 5, right panel), but at the same time reduced the average tax. All other
things equal, in 2011, the after-tax price decreases by about 3% if a car is 10% more fuel-
efficient. The charts in Figure 4 also show that, in the Netherlands, taxes for diesel cars are
persistently above those for petrol cars;14 in our results section, we will come back to the
effect of tax differentiation between petrol and diesel cars.
14
The Netherlands is atypical in the sense that registration taxes and fuel taxes are used as
instruments to segregate the car market. Diesel fuel taxes are low (relative to petrol) while
diesel registration taxes are high (relative to petrol). The tax scheme intends to separate longdistance drivers (who buy diesel cars) from short-distance drivers (who buy petrol cars).
16
Figure 4: Taxes per vehicle, dependent on CO2 emission intensity, for the Netherlands,
2001 (left panels) and 2010 (right panels), Petrol (upper) and Diesel (lower). Taxes are
measured relative to car prices.
17
Figure 5: Registration tax levels for typical vehicle, and tax dependence on CO2 emission
intensity, for the Netherlands, 2000-2011, Petrol (green solid) and Diesel (black dashed). 15
Table 1 below provides some additional summary statistics and the means for the first and
last sample years. Over 2001-2010, the average registration tax for diesel cars decreased
from 46 to 40 per cent (see footnote at table, and also see Table 5 in the appendix Section
9.2) while for petrol cars the registration tax rate decreased from an average of 39 to 35
percent. The extra tax paid for purchasing a high-emission vehicle has increased
substantially, however. In 2001, purchasing a diesel vehicle with 10 percent higher
emissions increased the registration tax rate by approximately 0.6 percentage point on
average. By 2010, this has increased to 1.4 percentage point. For some countries, the
elasticity of the registration tax rate with respect to emissions is negative. This does not
directly imply that fewer taxes are paid for polluting vehicles. If a more polluting car is
more expensive, then the absolute tax paid can increase while the tax rate paid can
decrease. 16
15
Note that the figure extends the period (2001-2010) over which we run the regressions. Also
note that the y-axis on the left panel should be interpreted as ‘elasticity’: ln(1+τ). Thus, a value
of 0.5 implies a tax of exp(0.5) = 65 per cent.
16
This can happen if part of the registration tax is independent of the car price. Indeed, results
from the linear model presented in the appendix, Table 5, show that in all countries, tax levels
(weakly) increase for more CO2 emission-intensive vehicles.
18
In 2001, the road tax rate is on average 2 percent of the vehicle’s (tax-exclusive)
purchase price, for both diesel and petrol cars. Several countries have no annual road tax.
The average elasticity of the annual tax rate with respect to CO2 emissions has changed
from being negative in 2001 to a positive value in 2010. Overall, there is a slight pattern
towards lower road tax rates, combined with a greater dependence of the tax rate on the
emissions of a car.
Table 1: Summary statistics for constructed tax levels and CO2 sensitivity for EU15*
Vehicle registration Diesel
tax rate
Petrol
Vehicle registration Diesel
tax rate, CO2
Petrol
sensitivity
Road tax rate
Road tax rate, CO2
sensitivity
*All
Diesel
Petrol
Diesel
Petrol
Mean
2001-2010
Std. dev.
0.35
0.26
0.16
0.07
0.19
-0.11
0.33
0.10
0.02
0.02
-0.004
-0.004
0.23
0.14
0.02
0.02
0.02
0.03
0.14
-0.02
0
0
-0.07
-0.09
Min
1.12
Max
0.98
0.66
0.43
0.06
0.08
0.003
0.02
2001
mean
2010
mean
0.38
0.34
0.06
0.14
0.33
0.10
0.02
0.02
-0.015
-0.011
0.30
0.13
0.02
0.02
0.003
0.004
numbers are based on a logarithmic representation. The average tax rate for diesel cars in 2001 was thus
exp(0.38)–1=0.46. See Table 5 in the appendix, Section 8.2, for the tax levels and CO2 sensitivity based on the linear
model.
Vehicle fiscal measures are correlated, also when we take out country and time fixed
effects. Petrol and diesel registration taxes move in tandem, both for the levels and CO2-
sensitivity. The same applies to the annual taxes, where correlations exceed 80%. 17 Petrol
and diesel fuel taxes are also positively correlated. The year fixed effects separate fuel price
developments from fuel tax changes. There is almost no correlation between the three
groups of tax instruments. For annual taxes, we see a very strong negative correlation
between the level of annual taxes and its CO2 sensitivity, implying that the set of annual
taxes are strongly multi-collinear, so that we must be careful when interpreting individual
coefficients for annual taxes. 18
17
18
See Table 7 in the appendix for details
The negative correlation between the level of annual taxes and its CO2 sensitivity is ‘natural’
in the following sense. If the level of annual taxes increase, typically they increase less then
19
5
Econometric strategy
The benchmark model estimates the dependence of the CO2 intensity of the new car fleet in
country c in year t (as in Figure 3), separately for diesel and petrol, 19 on the two
dimensions of the registration car taxes: its level and its CO2 sensitivity
𝐶𝑂2𝑖𝑛𝑡𝑐𝑡 = 𝛼1𝑐 + 𝛼2𝑡 + 𝛽1 𝑇𝐴𝑋𝑐𝑡 + 𝛽2 𝐶𝑂2𝑇𝐴𝑋𝑐𝑡 + ∑𝑘 𝜋𝑘 𝑍𝑐𝑘𝑡 + 𝜀𝑐𝑖𝑡 ,
(14)
where 𝛼1𝑐 and 𝛼2𝑡 are country and time dummies, and the country-time specific control
variables Z include income, the share of diesel cars in total sales, and gasoline taxes. 20 For
our preferred logarithmic model, we use logarithms for the dependent variable. In the
linear model (see appendix, Section 8.2), the dependent variable is measured in average
grams of CO2 emissions per km.
We add convergence patterns through the control variable, through
𝑍𝑐1𝑡 = 𝐶𝑂2𝑖𝑛𝑡𝑐0
𝑍𝑐2𝑡 = (𝑦𝑒𝑎𝑟𝑡 − 2001) × 𝐶𝑂2𝑖𝑛𝑡𝑐0 ,
(15)
(16)
where 𝐶𝑂2𝑖𝑛𝑡𝑐0 is the CO2 intensity of the new fleet in the base year 2001. Convergence
between countries is measured through a negative coefficient for the interaction term (16).
We assume there is no systematic correlation between observed fiscal vehicle policies and
unobserved policies such as vehicle retirement plans that could induce omitted variable
bias.
proportional with the car’s size, weight and price. Thus, annual taxes have a tendency to be
regressive. This is picked up by a negative coefficient for the CO2 sensitivity.
19
All variables are specific for diesel and petrol. We use both petrol and diesel independent
20
The fuel tax is estimated for each country-year-fuel type by fuel: tax=ln(1+{fuel tax
variables when we estimate the diesel share as dependent on car taxes.
level}/{fuel price}), where we take the fuel price as the average fuel price across the countries.
20
We estimate the model for both fuel types jointly and separately, with and without
the annual taxes. One of the control variables, the share of diesel cars, is itself dependent
on a country’s tax regime. As discussed in the introduction, diesel cars are typically less
CO2 intensive than petrol cars, and a high CO2 intensity of taxes may thus encourage
individuals to switch to diesel cars. To assess whether this affects our results, we reestimate the model without the diesel share.
6
Results
The main results are presented in Tables 2 and 3. Table 2 displays the results for the CO2
intensity for diesel and petrol cars respectively. Table 3 then reports the results for the CO2
intensity of all new purchased cars where petrol and diesel are aggregated, and reports the
dependence of the share of diesel cars on taxes.
6.1
Fuel-type specific effects
Starting with the CO2 intensity of new diesel cars, we find a clear significant effect
of registration taxes on CO2 emissions (see Table 2). Especially the CO2 sensitivity is an
effective instrument to change the characteristics of newly bought vehicles: a 1% increase
in CO2 sensitivity reduces the CO2 intensity by 0.04 to 0.1 percent. The effect is weaker
when we control for the diesel share, suggesting that part of the effect goes through the
changes in the diesel share. As we see in Table 3, a higher CO2 sensitivity of diesel
registration taxes increases the share of diesel cars. Buyers who decide to acquire a diesel
car as a substitute for a petrol car typically buy diesel cars that are smaller compared to the
average diesel car, while they substitute away from petrol cars that are larger compared to
the average petrol car (see the case study of Ireland, Rogan et al., 2011, Hennessy and Tol,
2011, Leinert et al., 2013). These consumers who substitute diesel cars for petrol cars
thereby reduce the average emissions from both diesel and petrol cars. The mechanism is
confirmed by the negative coefficients for diesel share in the diesel emissions (Table 2,
columns 1 and 3) and in the petrol emissions (Table 2, columns 5 and 7). Indeed, a closer
look at our data (not shown here) shows that diesel cars are on average 20 percent heavier
compared to petrol and the average weight for both diesel and petrol cars decreases with
an increase in the diesel share. Part of the emission reduction of new cars in the EU has
been achieved by lower registration taxes for diesel cars (Table 1 and Appendix, Table 5),
which translated in an increased share of diesel cars (Table 3, column 5 and Appendix,
21
Figure 6), which are typically more fuel efficient than petrol cars (Figure 1), and thus in
turn decreases the CO2 intensity of the average car (Table 3, column 1).
The registration tax level reduces the CO2 intensity of new diesel cars, yet only
significantly so when we account for the diesel share. In response to the observed decline
of diesel registration tax levels during the sample period, consumers of small diesel cars
switch to relatively less fuel-efficient, heavier diesel models, but there is also substitution
from petrol cars to small diesel cars. We find no significant effect for road taxes on the
emissions by diesel cars. Higher diesel fuel tax rates increase the fuel efficiency of newly
acquired vehicles, as expected (Burke and Nishitateno, 2013). In addition, we find higher
CO2 intensities with increasing income and a clear convergence pattern between EU
countries.
We find a similar pattern for petrol vehicles. The effect of CO2 tax sensitivity is
negative and significant: the average CO2 sensitivity in 2010 (0.13) reduces the CO2
intensity of new bought cars by about 2 percent. Again, the effect is weaker if we account
for the share of diesel cars. Higher taxes for fuel-intensive petrol cars will push potential
owners of large petrol cars to consider a diesel car as a substitute, thereby reducing the
size and emission-intensity of the average petrol car through the diesel-share variable. An
increase in the registration tax level reduces the CO2 intensity of newly acquired vehicles,
but the coefficients are insignificant. For petrol vehicles, annual road taxes receive a
significant coefficient, yet the signs are opposite to what is expected. Fuel taxes do not
show a significant effect for petrol car purchases. 21
This paper is one of the first including annual road taxes, in addition to registration
and fuel taxes, in the analysis of car purchase behaviour. We find that an increase in the
annual road tax level and CO2 sensitivity increases the CO2 intensity of new petrol cars. We
are not sure what causes this finding. It is not obvious that individuals account for future
annual tax expenses, as discussed in Section 2. In our regressions, even though the annual
tax rates enter significantly, excluding them from the regression has only little effect on the
coefficient for the other variables. Hence, we can interpret the other coefficients with
21
The insignificance is not driven by lack of variation as petrol taxes show up significantly in
Table 3.
22
confidence, and conclude that leaving annual taxes unaccounted for probably does not
greatly alter our conclusions.
6.2
Aggregate effects
Then consider the overall effect of car taxes on the new fleet emission intensity
(Table 3). The diesel share is the most important mediating variable: none of the policy
variables is significant when this share is included in the regression, though the joint effect
of more CO2-sensitive diesel and petrol taxes is significantly different from zero (columns 1
and 2). 22 The results in Table 3 allow us to assess the effect of the changes in registration
taxes on the diesel intensity. We subtract the log of taxes in 2001 from those in 2010
(Table 1) and multiply the differences with the coefficients in Table 3 (column 5). We
conclude that the changes in registration taxes have increased the diesel share by 6.5
percentage points. Using a similar calculation (but using column 2 from Table 3), we find
that the changes in registration taxes have reduced the CO2 intensity of the average new
car by 1.3% 23. 0.9 percentage points of this overall effect is explained by changes in the
diesel share. 24 The overall effects are modest; an explanation is that the large countries
with a major domestic car industry (France, Germany, Italy, United Kingdom), have
relatively low registration taxes that are almost independent of emission intensities.
When leaving out the diesel share, the diesel registration taxes stand out as the
most important determinants. Lower overall taxes for diesel cars increase the share of
diesel cars and thereby decrease average overall emissions, but also encourage existing
diesel drivers to switch to more polluting models. At the same time, a more CO2 sensitive
diesel registration tax favours small diesel cars, increasing the diesel share (column 5 and
22
As noted previously and presented in Table 7 in the appendix, policy measures for petrol and
diesel vehicles are strongly correlated. This inflates the standard errors of the individual
regressors in Table 3, columns 1-4. When testing, we find in column 1 and 2 that the sum of the
diesel and petrol coefficients for the CO2 sensitivity of registration taxes is significantly
different from zero.
23
We use more decimals than shown for the numbers in Table 1, so the reader’s calculation
24
We multiply 6.5 by the coefficient –0.143 in in Table 3, column 1.
may give a slightly different result.
23
6) and decreasing overall emissions (column 3 and 4). Interestingly, the changes in
registration taxes over the period 2001-2010 have caused extant diesel drivers to choose
more CO2-intensive cars on average. For these drivers, the effect of lower registration tax
levels in 2010 compared to 2001 dominates the effect of the increased CO2 sensitivity.
Along the same lines, we find that higher petrol fuel taxes tend to increase the diesel
share and reduce the fleet’s emission intensity (columns 2,4,5,6), while diesel fuel taxes
tend to decrease the share of diesel cars, increasing the average emissions (column 2 and
4), though the effect is weak. The finding is consistent with Ryan et al. (2009), but a subtle
and important distinction from the general conclusion in the literature that higher petrol
prices tend to lead to more fuel efficient cars (Davis and Kilian 2011, Burke and
Nishitateno 2013, Klein and Linn 2013).
6.3
Transmission mechanisms
Finally, we present a brief assessment of the transmission channels through which fiscal
car taxes change emissions. We have already seen that consumers switch between petrol
and diesel cars, in response to tax measures, but within a fuel type, they can also respond
to tax measures by switching to lighter cars with less powerful engines, or alternatively,
they can choose for cars with more fuel efficient engines while keeping the preferred car
specifications unaffected (Fontanas and Zamaras, 2010).
In Table 4 we present, for diesel and petrol separately, the effect of fiscal measures
on the CO2 intensity with and without additional controls for average vehicle mass and
engine power. If controlling for mass or power reduces the (absolute) value of the policy
coefficient, this can be taken as an indication that part of the policy’s effect is transmitted
through the car features. Next, we estimate the direct effect of fiscal policies on average
vehicle mass and engine power. In all models, we control for convergence, income, time
and country fixed effects.
To allow easy comparison, columns 1 and 5 in Table 4 reproduce Table 2 columns
1 and 5 respectively. Column 2 and 6 confirm that larger cars with more powerful engines
have higher emission intensities. For diesel cars, registration taxes do not significantly
affect average mass or engine power of newly purchased vehicles, although adding these
features does slightly reduce the (absolute) coefficient on registration taxes in column 2
compared to column 1. A similar effect is found for the CO2 sensitivity of diesel registration
taxes. One possible interpretation of this finding is that higher and more CO2-sensitive
24
diesel registration taxes push the technology frontier for cars, providing the same qualities
(mass and horsepower) to the consumers, at lower CO2 emissions. For petrol cars, the
effects of registration taxes appear to be transmitted through the car features: higher (CO2
sensitivity of) registration taxes reduce the average mass and horse power of newly
purchased vehicles, even when controlling for the diesel share. There is less indication of a
technology effect, and more evidence of switch in the type of cars bought by consumers.
We note that the effects of income on CO2 intensities appear to be fully transmitted
through car features, both for diesel and petrol cars. Such an outcome is intuitive, as
increasing income will be used mainly to increase the level of desirable features. The effect
of income on CO2 intensity does not become significantly negative when controlling for
mass and horse power, so we find no evidence that consumers use income increases to
purchase more environmentally friendly cars. For diesel cars, the effect of diesel fuel taxes
is also fully transmitted through the car features.
25
Table 2. Dependence of new car fleet emissions on taxes, per fuel type
Dependent variable
TAX registration
(1)
–0.165*
(log) CO2 intensity diesel
(2)
(3)
–0.021
–0.163*
(4)
–0.028
(5)
–0.086
(log) CO2 intensity petrol
(6)
(7)
–0.030
–0.073
(8)
–0.028
CO2TAX registration
–0.045
–0.099***
–0.095***
–0.119**
–0.136***
–0.136***
TAX road
–0.334
0.157
1.855***
1.624***
CO2TAX road
–0.240
0.369
1.014***
1.018***
Diesel share
–0.155***
(log) income
0.128*
0.251***
0.136**
0.233***
0.132***
0.196***
0.098**
0.150***
Fuel tax rate
–0.226***
–0.302***
–0.225***
–0.303***
0.034
–0.048
0.079
0.004
Convergence
–0.030**
–0.051***
–0.032**
–0.048***
–0.020**
–0.029***
–0.049*
–0.149***
–0.069***
–0.124**
–0.059***
–0.022**
–0.030***
Time dummies
Yes
yes
Yes
Yes
Yes
Yes
yes
Country dummies
Yes
yes
Yes
Yes
Yes
Yes
yes
Yes
Observations
150
150
150
150
150
150
150
150
0.929
0.914
0.975
0.973
0.973
0.970
R-squared
0.929
0.915
Significance: *** p<0.01, ** p<0.05, * p<0.1
26
Yes
Table 3. Dependence of car emissions (aggregated over fuels) and diesel share on taxes.
Dependent variable
(1)
–0.107
–0.055
(log) CO2 intensity overall
(2)
(3)
–0.142
–0.079
–0.065
–0.056
TAX registration diesel
0.436
0.389
0.071
–1.034
0.335
0.237**
CO2TAX registration diesel
–0.027
–0.063**
TAX road diesel
0.565
2.272***
–14.43***
CO2TAX road diesel
0.178
0.432
–1.342
Diesel share
–0.143***
(log) income
0.066
0.157***
0.045
0.148***
–0.591***
–0.693***
Fuel tax rate diesel
0.005
0.070*
–0.033
0.031
–0.421
–0.251
Fuel tax rate petrol
–0.012
–0.183**
0.072
–0.180**
1.172***
1.156***
Convergence
–0.019**
–0.030***
–0.020**
–0.049***
TAX registration petrol
CO2TAX registration petrol
TAX road petrol
CO2TAX road petrol
Diesel share
(6)
0.279
–0.030
(4)
–0.109
–0.047
(5)
0.187
0.096
0.033
0.188*
12.45***
0.363
–1.164***
–1.094***
–0.020
–0.057**
0.249***
0.258**
–0.155***
Time dummies
yes
Yes
Yes
Yes
yes
Country dummies
yes
Yes
Yes
Yes
yes
Yes
150
150
150
150
150
0.974
0.978
0.968
0.958
0.923
150
Observations
R-squared
0.979
Significance: *** p<0.01, ** p<0.05, * p<0.1
27
Yes
Table 4. Transmission of fiscal policies to CO2 intensity
Dependent variable
(logs)
CO2
(1)
diesel
mass
(3)
horse power
(4)
CO2
(5)
petrol
Mass (log)
Horse power (log)
TAX registration
-0.165*
CO2
(2)
0.772***
0.288***
-0.024
-0.014
-0.185
-0.086
CO2
(6)
0.516***
0.143***
-0.016
mass
(7)
horse power
(8)
-0.097
-0.229
CO2TAX registration
-0.045
-0.038**
0.002
-0.024
-0.119**
-0.000
-0.156***
-0.260***
TAX road
-0.334
-0.102
-1.505**
0.823
1.855***
0.493
1.594***
3.580***
CO2TAX road
-0.240
-0.130
-0.684*
0.546
1.014***
0.193
1.038***
1.896***
Diesel share
-0.155***
-0.037*
-0.086**
-0.104**
-0.069***
-0.042***
-0.042
-0.045
(log) income
0.128*
-0.016
0.114*
0.193**
0.132***
-0.018
0.166***
0.420***
Fuel tax rate
-0.226***
0.031
-0.240***
-0.294**
0.034
0.051
-0.023
0.034
Convergence
-0.030**
-0.048***
-0.003
-0.008
-0.020**
-0.006
-0.014*
-0.010
Time dummies
Yes
Yes
yes
Yes
Yes
Yes
yes
Yes
Country dummies
Yes
Yes
yes
Yes
Yes
Yes
yes
Yes
Observations
150
150
150
150
150
150
150
150
0.976
0.876
0.929
0.975
0.992
0.952
0.965
R-squared
0.929
Significance: *** p<0.01, ** p<0.05, * p<0.1
28
7
Discussion
We find empirical evidence that fiscal vehicle policies significantly affect emission
intensities of new bought cars. Increasing CO2-sensitivity of registration taxes and higher
fuel taxes lead to the purchase of more fuel efficient cars, but higher annual road taxes
have no or an adverse effect. The former is consistent with the literature; the latter is
counter-intuitive, possibly because annual road taxes are not salient, but the high
collinearity between annual road taxes may also play a role. We decomposed the vehicle
registration tax rate into two variables, the level and CO2-sensitivity, and found that
especially the CO2-sensitivity is an important determinant of the emission intensity of new
cars. A one percent increase in the CO2 sensitivity of vehicle purchase taxes reduces the
CO2 intensity of the average new vehicle by 0.04 to 0.13 percent. The changes in
registration taxes from 2001 to 2010 have reduced the CO2 emission intensity of the
average new car by 1.3%. The diesel-petrol substitution induced by changes in the relative
taxes for diesel versus petrol cars is an important factor for the average fleet’s fuel
efficiency. We also find higher CO2 intensities with increasing income and a clear
convergence pattern between EU countries.
There is a clear positive potential for fiscal instruments as part of the set of policy
measures aimed at reducing CO2 emissions from cars. 25 Our findings thus support the
European Commission’s third policy pillar. Yet, we should not overstate the contribution of
registration taxes. The overall effect of the registration tax changes that we identify, a 1.3%
improvement of fuel efficiency, is small compared to the overall achievement over the
period observed (Figure 1). Innovation and other policy instruments have played a
substantial role. In that context, it is important to understand that various policy
instruments can strengthen, but also counter each other. In the European Directive
EC/443/2009 car manufacturers are evaluated (from 2015 onwards) based on their
average emissions of cars sold across all EU countries. Increased sales of fuel efficient cars
in one country thus allows manufactures to sell more fuel inefficient cars in other
countries. The principle, sometimes referred to as a ‘waterbed-effect', implies that
environmental gains from fiscal national policies can leak away as the sale of more fuel-
25
See Burke (2014) for a broader discussion.
29
efficient cars in a country with a fiscal regime that puts a large premium on CO2 emissions,
is countered by the sale of more fuel-intensive cars in other countries. National fiscal
policies, aimed at the demand side, and in line with the third pillar of EU-policies, might
thus be less effective conditional on the effectiveness of the first pillar of EU-policy, aimed
at the supply of fuel efficient cars throughout the EU.Given an exogenously set ceiling for
the EU-wide CO2 emissions, there is no clear economic gain from a diversified fiscal regime
between EU countries, while there are social costs (Hoen and Geilenkirchen, 2006). Indeed,
a few years ago, the EU proposed to harmonize vehicle taxes in the EU, but the proposal
was rejected by the Member States. We also mention a few other potential disadvantages
of fiscal support of fuel efficient cars.
In this paper, we focus on the average emission intensity of new cars. Reducing taxes for
small, fuel-efficient cars can lead to scale effects (i.e. more cars) and intensity-of-use effects
(i.e. more kilometres per car). Konishi and Zhao (2014) show that in a green tax reform in
Japan, this scale effect offset the composition effect (i.e. a bigger share of fuel-efficient cars)
by approximately two third. In addition, there is a rebound effect. Fuel-efficient cars are
cheaper to drive, and a portion of the CO2 gains by CO2 -based vehicle purchase tax is lost
as the fuel-efficient cars increase car travel demand (Khazoom, 1980). The existence of the
effect is undisputed, but its magnitude remains an issue of debate (see e.g. Brookes, 2000,
Binswanger, 2001, Sorrell and Dimitropoulos, 2008). Frondel and Vance (2014) estimated
that 44-71% of potential energy savings from efficiency improvements in Germany
between 1997 and 2012 were lost due to increased driving. The rebound effect may be
mitigated if part of the increase in sales of new, clean cars is due to consumers sooner
retiring their less-efficient cars.
Of the policies aimed at reducing CO2 emissions, excise fuel duties most directly
target the environmental objective, specifically since the use of the car is accountable for
about 80% of CO2 emissions in its life-cycle (E. Gbeghaje-Das 2013). Fuel excise duties are
also closer to the ‘polluter pays-principle’, one of the leading principles of European
Environmental Policy (European Parliament and Council, 2004). Taxing fuels would lead to
more efficient cars and lower mileage without rebound effects (Cropper and Chugh, 2014),
making it the preferred instrument for reducing road transport emissions. Yet significant
fuel tax increases are politically costly.
There are also secondary effects of fiscal policies. When consumers choose lighter
cars that are more fuel efficient, not only CO2 emissions fall but emissions of NOx and PM10
30
as well. A weight reduction of 10% results in a decrease of the emission of NOx with 3-4%
(Nijland et al., 2012). On the other hand, substituting diesel cars for petrol cars improves
CO2 fuel efficiency by about 10-20%, yet increases the emissions of NOx (Nijland et al.,
2012). In the case of PM10 the situation is not clear, as modern petrol cars with direct
injection might emit more PM10 than modern diesel cars (Köhler, 2013). Lighter cars also
reduce fatalities for drivers of other vehicles, pedestrians, bicyclists, and motorcyclists
(Gayer 2004, White 2004). The design of the fiscal regime, encouraging lighter cars or
encouraging diesel cars, can alter the secondary effects substantially.
We used CO2 emission data according to the NEDC guidelines. It is known that the
tests typically report lower emissions compared to realistic conditions, especially for cars
that score very well at the tests (Ligterink and Bos, 2010, Ligterink and Eijk, 2014).
Moreover, the gap between test results and realistic estimates for normal use have
increased over time; from about 8% in 2001 to 21% in 2011, with a particularly strong
increase since 2007 (Mock et al. 2012, ICCT, 2014). The gap between test values and
estimates of realistic use values also affects the estimated emission of air pollutants,
particularly the emissions of NOx from diesel cars (e.g. Hausberger, 2006, Vonk and
Verbeek, 2010). To continue the use of test-cycles therefore requires an update of
procedures and improvement of their reliability as predictor of real-life use.
Finally, we mention three limitations of our study. We proxy the fiscal treatment of
personal vehicles, assuming that taxes change continuously with CO2 emissions. Yet, there
are indications that consumers are more sensitive to discrete price increases, such as tax
breaks for cars that meet specific criteria (see e.g. Finkelstein, 2009, Klier and Linn, 2012,
Kok, 2013). This study did not explicitly model these elements of tax design. Second, about
half of the new sales in Europe are company cars (Copenhagen Economics, 2010). One of
the reasons for their widespread use is their beneficial tax treatment (Gutierrez-iPuigarnau and van Ommeren, 2011), including implicit subsidies as employees often do
not bear the variable costs of private use (Copenhagen Economics, 2010). Therefore,
private consumers and business consumers react differently to price signals such as fiscal
rules and fuel taxes. We do not have available data on the two separate markets and must
leave this topic to future research. Third, we did not consider other fiscal measures such as
the scrap subsidies which had major effects on sales in various countries, though the
effects on the fuel efficiency is considered limited (Leheyda and Verboven, 2013).
31
8
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We
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Appendix
Loglinear detailed model of Section 3.2
construct
the
country-car-year
variables
𝐿𝑂𝐺𝐶𝑂2𝑖𝑡=ln(𝐶𝑂2𝑖𝑡)
and
𝐿𝑂𝐺𝑇𝐴𝑋𝑐𝑖𝑡=ln(1+𝜏𝑐𝑖𝑡) from our database, and subsequently construct the country
averages (equations (8) and (9)), denoted by a bar over the variables:
�����������𝑐𝑡 = ∑𝑖 𝛿𝑐𝑖𝑡 𝐿𝑂𝐺𝐶𝑂2𝑖𝑡
𝐿𝑂𝐺𝐶𝑂2
∑
�����������𝑐𝑡 =
𝐿𝑂𝐺𝑇𝐴𝑋
𝑖 𝛿𝑐𝑖𝑡
∑𝑖 𝛿𝑐𝑖𝑡 𝐿𝑂𝐺𝑇𝐴𝑋𝑐𝑖𝑡
∑𝑖 𝛿𝑐𝑖𝑡
36
(17)
(18)
We subsequently calculate the CO2-sensitivity of the tax (10), LOGCO2TAXct, by comparing
how much taxes increase when CO2 emissions increase, on average, and weighted:
𝐿𝑂𝐺𝐶𝑂2𝑇𝐴𝑋𝑐𝑡 =
������������𝑐𝑡 )
∑𝑖 𝑤𝑐𝑖𝑡 (𝐿𝑂𝐺𝑇𝐴𝑋𝑐𝑖𝑡 −𝐿𝑂𝐺𝑇𝐴𝑋
������������𝑐𝑡 )
∑𝑖 𝑤𝑐𝑖𝑡 (𝐿𝑂𝐺𝐶𝑂2𝑐𝑖𝑡 −𝐿𝑂𝐺𝐶𝑂2
(19)
where weights are given by the deviation from the average CO2 intensity (11):
𝑤𝑐𝑖𝑡 = (𝐿𝑂𝐺𝐶𝑂2𝑐𝑖𝑡 − �����������
𝐿𝑂𝐺𝐶𝑂2𝑐𝑡 )
(20)
We then construct the (virtual) tax rate LOGTAXct that would apply to a car with a CO2emission profile that is typical for the aggregate of all countries (12) (13):
� 𝑡 = ∑𝑐,𝑖 𝛿𝑐𝑖𝑡𝐿𝑂𝐺𝐶𝑂2𝑐𝑖𝑡
𝐿𝑂𝐺𝐶𝑂2
∑
𝑐,𝑖 𝛿𝑐𝑖𝑡
� 𝑡 − 𝐿𝑂𝐺𝐶𝑂2
�����������𝑐𝑡 + 𝐿𝑂𝐺𝐶𝑂2𝑇𝐴𝑋𝑐𝑡 (𝐿𝑂𝐺𝐶𝑂2
�����������𝑐𝑡 )
𝐿𝑂𝐺𝑇𝐴𝑋𝑐𝑡 = 𝐿𝑂𝐺𝑇𝐴𝑋
(21)
(22)
The two constructed variables LOGTAXct and LOGCO2TAXct, are used as independent
variables explaining the average emission intensity of the new car fleet (14). Note that the
country-average CO2 intensity constructed in (8) or (17) is not the same variable used in
the econometric regression, used as independent variable in Section 4 (14). The country-
average CO2 intensity in (8) or (17) is measured only for those car types for which we have
price and tax data, and its purpose is solely to construct the CO2 sensitivity of car taxes in
(10) or (19). The country-average CO2 intensity used in Section 4 (14) is from an
independent source, and is based on all car sales in a country-year; it is the independent
variable that we explain using the country tax variables constructed in Section 3.2.
9.2
Linear model
In the main text, we characterized a country’s tax system by two coefficients: the average
rate, and its CO2 sensitivity, which is defined as elasticity of the tax rate with respect to
CO2 emissions. In this appendix, we take a linear approach. Here, the CO2 sensitivity is
instead defined as the increase in the tax level for a given increase in CO2 emissions (in
grams per km). To decompose the tax in these elements, we estimate
37
𝑝
�𝑡 )
𝜏𝑐𝑖𝑡 = 𝑇𝐴𝑋𝑐𝑡 𝑝𝑐𝑖𝑡 + 𝐶𝑂2𝑇𝐴𝑋𝑐𝑡 (𝐶𝑂2𝑐𝑖𝑡 − 𝐶𝑂2
𝑝
where 𝜏𝑐𝑖𝑡 is the tax paid (in euro’s) for vehicle i in country c at time t, 𝑝𝑐𝑖𝑡 is the tax
�𝑡 the average
exclusive purchase price, 𝐶𝑂2𝑐𝑖𝑡 the vehicle CO2 emission in g/km and 𝐶𝑂2
time t CO2 emissions in g/km. We then characterize a tax system by 𝑇𝐴𝑋𝑐𝑡 , which is the
average tax rate as a percentage of the purchase price, and 𝐶𝑂2𝑇𝐴𝑋𝑐𝑡 which is the
additional tax, in euro’s, per g/km additional CO2 emissions. 26
Table 4 presents the summary statistics equivalent to Table 1, as the numbers in this table
are potentially easier to interpret. Consistent with the results for the logarithmic model, we
find that from 2001 to 2010, the average registration taxes have fallen, yet its CO2
sensitivity has increased, for petrol and diesel cars. For example, for diesel cars, the
average registration tax fell from 53 percent in 2001 to 44 percent in 2010. In 2001
however, emitting an additional 10 gCO2/km would increase the tax by 88 euros on
average. In 2010, this has increased to 382 euros. Adjusting the decomposition slightly
alters the estimation of the average tax rate. In Table 1, the 2001 (2010) diesel registration
tax rate is 46 (40) percent, for petrol this is 39 (34) percent; in Table 4 these rates are
approximately 7 percentage points higher.
26
Note that this simultaneous estimation of 𝑇𝐴𝑋𝑐𝑡 and 𝐶𝑂2𝑇𝐴𝑋𝑐𝑡 is not a departure from
the decomposition strategy in Section 4.2, as the decomposition in the main text is
�𝑡 ), with all variables as
equivalent to estimating 𝜏𝑐𝑖𝑡 = 𝑇𝐴𝑋𝑐𝑡 + 𝐶𝑂2𝑇𝐴𝑋𝑐𝑡 (𝐶𝑂2𝑐𝑖𝑡 − 𝐶𝑂2
defined in Section 4.2.
38
Table 5: Summary statistics for constructed coefficients for EU15 – linear model*
Vehicle registration tax Diesel
rate
Petrol
Diesel
Vehicle registration tax,
CO2 sensitivity
Petrol
Road tax rate
Road tax, CO2 sensitivity
*Tax
Diesel
Petrol
Diesel
Petrol
2001-2010
Mean
Std. Dev
0.47
0.46
0.50
Min
Mean
Mean
1.93
0.46
0.42
0.16
2.23
17.4
33.74
-22.31
92.88
0.02
0.01
23.2
0.01
–0.48
–0.83
34.62
0.02
2.43
3.04
-2.73
0
0
-8.88
-10.71
2010
Max
0.53
0.15
2001
0.53
8.8
127.72
20.5
0.07
0.02
0.05
1.10
1.04
0.02
–1.38
–1.48
0.44
38.2
32.3
0.02
0.01
0.28
–0.02
rates are measured as percentage of the tax exclusive purchase price, CO2 sensitivity in euro per gCO2/km.
Note: For this table, data are not weighted.
With this decomposition, we consider the effect of the vehicle registration tax rate, and the
CO2 sensitivity of the tax paid on the average CO2 intensity of newly purchased vehicles.
Results are presented in Tables 6 and 7. Since we now take the level of the additional tax
on CO2 emissions, and the level of the average CO2 intensity of newly purchased vehicles
interpretation is slightly different compared to Tables 2 and 3. Take for example the first
column of Table 6. Here, a 10 percentage point increase in the vehicle registration tax rate
is expected to reduce the CO2 intensity of diesel cars by 2.2 gCO2/km. Similarly, the
(insignificant) coefficient of -0.005 on CO2TAX registration implies that a 10 euro increase
in the effective registration tax rate on CO2 emissions for diesel cars, is expected to reduce
the average CO2 intensity of diesel cars by 0.05 gCO2/km. In terms of sign and significance,
results are in line with the logarithmic model in the main text.
39
Table 6. Dependence of new car fleet emissions on taxes, per fuel type, linear model
TAX registration
CO2TAX registration
(1)
-22.51***
-0.005
CO2 intensity diesel
(2)
(3)
-7.973
-20.42***
-0.032*
-0.0004
TAX road
74.23
CO2TAX road
-0.254
Diesel share
-30.04***
(log) income
11.76
Dependent variable
(5)
0.287
-0.053**
CO2 intensity petrol
(6)
(7)
2.892
0.395
-0.072***
-0.067***
101.1
194.8**
120.3
-0.087
0.638*
0.526
(4)
-6.329
-0.033*
-29.04***
36.76***
16.68*
-9.748**
38.64***
(8)
2.620
-0.079***
-7.828**
21.69***
29.59***
19.16***
25.92***
Fuel tax rate
-18.70*
-35.50***
-20.92**
-36.71***
1.168
-5.332
3.633
-2.812
Convergence
-0.014
-0.043**
-0.020
-0.045***
-0.040***
-0.047***
-0.044***
-0.049***
Time dummies
Yes
Yes
Yes
Yes
yes
Yes
Yes
Yes
Country dummies
Yes
Yes
Yes
Yes
yes
Yes
Yes
Yes
Observations
R-squared
150
0.932
150
0.909
150
150
150
150
150
150
0.930
0.908
0.975
0.974
0.974
0.973
Significance: *** p<0.01, ** p<0.05, * p<0.1
40
Table 7. Dependence of car emissions (aggregated over fuels) and diesel share on taxes,
linear model.
Dependent variable
(1)
-6.381
-0.010
CO2 intensity overall
(2)
(3)
-5.691
-5.500
-0.030
-0.013
TAX registration diesel
-47.73
0.525
6.649
-286.5***
0.630
12.27*
CO2TAX registration diesel
-0.016
-0.027*
TAX road diesel
267.4***
457.3***
CO2TAX road diesel
0.128
0.080
Diesel share
-20.73***
(log) income
12.74**
25.18***
10.04*
27.51***
-0.623***
-0.799***
Fuel tax rate diesel
-6.036
-3.061
-9.646
-4.152
-0.062
-0.016
Fuel tax rate petrol
3.758
-10.88
7.313
-18.06**
0.532***
0.725***
Convergence
-0.029***
-0.042***
-0.039***
-0.064***
TAX registration petrol
CO2TAX registration petrol
TAX road petrol
CO2TAX road petrol
Diesel share
(6)
-0.035
0.0006
(4)
-5.859
-0.027
(5)
-0.134
0.001
6.116
13.04*
11.78***
-0.019*
-0.243
-0.310
-0.010
-0.022
0.0005
0.0006
-12.09***
0.019**
-23.93***
Time dummies
yes
Yes
Yes
yes
Yes
Country dummies
yes
Yes
Yes
yes
Yes
yes
150
150
150
150
150
150
0.976
0.979
0.970
0.952
0.921
Observations
R-squared
0.981
Significance: *** p<0.01, ** p<0.05, * p<0.1
9.3
Additional figures
Figure 6: Share of diesel cars in new fleet.
41
yes
Table 7: Correlation between fiscal vehicle measures
Registration Petrol level
CO2
Diesel level
CO2
Annual
Petrol level
CO2
Diesel level
CO2
Fuel
Petrol
Diesel
Registration
Petrol
Diesel
level
CO2
level
CO2
1.00
-0.38
1.00
0.67
-0.16
1.00
-0.21
0.61
0.24
1.00
0.07
-0.09
0.13
-0.07
-0.05
0.10
-0.13
0.12
0.00
-0.09
0.08
-0.10
0.08
0.13
0.02
0.18
-0.03
0.09
-0.04
0.01
-0.03
0.10
0.03
0.07
Annual
Petrol
Diesel
level
CO2
level
CO2
1.00
–0.89
0.85
–0.75
0.04
0.14
1.00
–0.75
0.84
-0.07
-0.06
1.00
–0.75
0.04
0.15
1.00
-0.13
-0.10
Fuel
Petrol
Diesel
1.00
0.75
Correlations for variables after taking out time and country fixed effects. In bold those >0.5. Annual taxes are multi-collinear.
42
1.00